Answered

GPU computing doesn't work with timedelaynet, inputDelays != 0:0

Currently the GPU implementation of training does not parallelize for single series. If you have a long series and can break it...

GPU computing doesn't work with timedelaynet, inputDelays != 0:0

Currently the GPU implementation of training does not parallelize for single series. If you have a long series and can break it...

alrededor de 4 años ago | 0

Answered

How can I extract the values of weights and biases after each training epoch?

Greg is right, the function to get weights outside of a training function is getwb. Within a training function it is slightly...

How can I extract the values of weights and biases after each training epoch?

Greg is right, the function to get weights outside of a training function is getwb. Within a training function it is slightly...

más de 4 años ago | 0

Answered

GPU training of neural network with parallel computing toolbox unreasonably slow, what am I missing?

Getting a speed up with a GPU requires a couple things: 1) The amount of time spent in gradient calculations (which happen on...

GPU training of neural network with parallel computing toolbox unreasonably slow, what am I missing?

Getting a speed up with a GPU requires a couple things: 1) The amount of time spent in gradient calculations (which happen on...

más de 4 años ago | 0

| accepted

Answered

When using GPU with neural net, I run out of shared memory per block; is there a way to handle?

I was able to reproduce your error. In MATLAB 13a the nndata2gpu array transformation is no longer required and if gpuArray is u...

When using GPU with neural net, I run out of shared memory per block; is there a way to handle?

I was able to reproduce your error. In MATLAB 13a the nndata2gpu array transformation is no longer required and if gpuArray is u...

más de 6 años ago | 0

Solved

Column Removal

Remove the nth column from input matrix A and return the resulting matrix in output B. So if A = [1 2 3; 4 5 6]; and ...

más de 7 años ago

Solved

Find the sum of all the numbers of the input vector

Find the sum of all the numbers of the input vector x. Examples: Input x = [1 2 3 5] Output y is 11 Input x ...

más de 7 años ago

Answered

Delays in the Neural Network Toolbox

Yes you are correct. The way you have set delays the network at each time step will be responsive to the current fuzzy time of ...

Delays in the Neural Network Toolbox

Yes you are correct. The way you have set delays the network at each time step will be responsive to the current fuzzy time of ...

casi 8 años ago | 0

| accepted

Answered

Architecture of the neural network by nftool?

You have correctly understood how the main part of the neural network works, however, the inputs and outputs of the neural netwo...

Architecture of the neural network by nftool?

You have correctly understood how the main part of the neural network works, however, the inputs and outputs of the neural netwo...

casi 8 años ago | 0

| accepted

Answered

Disable Spacebar Command for Neural Network

You can turn off the training window (and therefore not have a stop button to accidentally trigger) with this command before cal...

Disable Spacebar Command for Neural Network

You can turn off the training window (and therefore not have a stop button to accidentally trigger) with this command before cal...

más de 8 años ago | 0

Answered

Combine parallel toolbox and neural network toolbox

Currently parallel computing can be used to train multiple networks on different MATLAB workers at the same time. This speeds u...

Combine parallel toolbox and neural network toolbox

Currently parallel computing can be used to train multiple networks on different MATLAB workers at the same time. This speeds u...

más de 8 años ago | 0

Answered

Neural Nets for Classification

Yes, PATTERNNET is recommended for classification problems. TRAINLM is a good training function for most problems. For small...

Neural Nets for Classification

Yes, PATTERNNET is recommended for classification problems. TRAINLM is a good training function for most problems. For small...

más de 8 años ago | 0

| accepted

Answered

Knowing the Weights in Matlab

The biases for each layer i are net.b{i}. So for a two layer network the biases are net.b{1} and net.b{2}. The weights to la...

Knowing the Weights in Matlab

The biases for each layer i are net.b{i}. So for a two layer network the biases are net.b{1} and net.b{2}. The weights to la...

más de 8 años ago | 2

| accepted

Answered

Crossvalidation of Neural Networks

I am not sure I understand your question but perhaps this will help. If you want to divide your data set into a design set an...

Crossvalidation of Neural Networks

I am not sure I understand your question but perhaps this will help. If you want to divide your data set into a design set an...

más de 8 años ago | 0

Answered

NARX perform additional tests on network: from GUI to code

To apply the network to new data after training do the following: inputSeries2 = { ... your new input series ... }; [inp...

NARX perform additional tests on network: from GUI to code

To apply the network to new data after training do the following: inputSeries2 = { ... your new input series ... }; [inp...

más de 8 años ago | 1

Answered

Unable to load trained network, maybe versionconflict

Unfortunately the R2010a version of the toolbox cannot support neural networks created with R2010b or later versions of the tool...

Unable to load trained network, maybe versionconflict

Unfortunately the R2010a version of the toolbox cannot support neural networks created with R2010b or later versions of the tool...

más de 8 años ago | 0

Answered

Neural Network - Multi Step Ahead Prediction

Here is an example that may help. A NARX network is trained on series inputs X and targets T, then the simulation is picked up ...

Neural Network - Multi Step Ahead Prediction

Here is an example that may help. A NARX network is trained on series inputs X and targets T, then the simulation is picked up ...

más de 8 años ago | 1

Answered

How to forecast with Neural Network?

You can convert the NARXNET from open-loop to closed-loop form to predict ahead any number of timesteps for which you have data ...

How to forecast with Neural Network?

You can convert the NARXNET from open-loop to closed-loop form to predict ahead any number of timesteps for which you have data ...

más de 8 años ago | 3

Answered

Different results by backpropagation algorithm using different MatLab versions (2008 and 2010)

First, I assume you are setting the random seed before running this code to try and reproduce exact results? Otherwise, every r...

Different results by backpropagation algorithm using different MatLab versions (2008 and 2010)

First, I assume you are setting the random seed before running this code to try and reproduce exact results? Otherwise, every r...

casi 9 años ago | 0

| accepted

Answered

Self Organizing Maps

The prototype pattern for each neuron is its weight vector. To see all the neurons' weight vectors: net.IW Each row rep...

Self Organizing Maps

The prototype pattern for each neuron is its weight vector. To see all the neurons' weight vectors: net.IW Each row rep...

casi 9 años ago | 0

| accepted

Answered

how to use weights and thresholds from Neural Network toolbox

You need to first preprocess inputs, then post process outputs as follows: xx = [0:0.5:5] for i=1:length(net.inputs{1}.p...

how to use weights and thresholds from Neural Network toolbox

You need to first preprocess inputs, then post process outputs as follows: xx = [0:0.5:5] for i=1:length(net.inputs{1}.p...

casi 9 años ago | 0

Answered

How do I display the connection weights after each epoch for a perceptron network using MATLAB code?

The function PLOTWB displays weights and biases graphically. plotwb(net) You can attach this function to any network obj...

How do I display the connection weights after each epoch for a perceptron network using MATLAB code?

The function PLOTWB displays weights and biases graphically. plotwb(net) You can attach this function to any network obj...

casi 9 años ago | 0

| accepted

Answered

Change preprocessing parameter in neural network

You can try this workaround: net = struct(net); net.inputs{1}.processParams{2}.ymin = 0.1; net = network(net);

Change preprocessing parameter in neural network

You can try this workaround: net = struct(net); net.inputs{1}.processParams{2}.ymin = 0.1; net = network(net);

casi 9 años ago | 0

| accepted

Answered

Plant model

The function GENSIM converts a neural network once it has been trained in MATLAB into an equivalent Simulink block diagram.

Plant model

The function GENSIM converts a neural network once it has been trained in MATLAB into an equivalent Simulink block diagram.

casi 9 años ago | 1

| accepted

Answered

Neural network performance function, weighted sse, and false alarms

Error weights can help you set which targets are most important to get correct, or equivalently, more costly to get wrong. Le...

Neural network performance function, weighted sse, and false alarms

Error weights can help you set which targets are most important to get correct, or equivalently, more costly to get wrong. Le...

casi 9 años ago | 1

Answered

How to use NNTOOL

If the input has 300 hundred elements, and the hidden layer has 50 neurons, then each of the 300 neurons will have a connection ...

How to use NNTOOL

If the input has 300 hundred elements, and the hidden layer has 50 neurons, then each of the 300 neurons will have a connection ...

casi 9 años ago | 0